class_docstr: Logger for comet.
  
  Adds interface for `add_image` in the logger rather than calling the experiment object.
  Note:
      Same as the CometLogger provided by PyTorch Lightning and the doc string is reproduced below.
  
  Track your parameters, metrics, source code and more using
  `Comet <https://www.comet.com/site/products/ml-experiment-tracking/?utm_source=anomalib&utm_medium=referral>`_.
  
  Install it with pip:
  
  .. code-block:: bash
  
      pip install comet-ml
  
  Comet requires either an API Key (online mode) or a local directory path (offline mode).
  
  Args:
      api_key: Required in online mode. API key, found on Comet.ml. If not given, this
          will be loaded from the environment variable COMET_API_KEY or ~/.comet.config
          if either exists.
      save_dir: Required in offline mode. The path for the directory to save local
          comet logs. If given, this also sets the directory for saving checkpoints.
      project_name: Optional. Send your experiment to a specific project.
          Otherwise will be sent to Uncategorized Experiments.
          If the project name does not already exist, Comet.ml will create a new project.
      rest_api_key: Optional. Rest API key found in Comet.ml settings.
          This is used to determine version number
      experiment_name: Optional. String representing the name for this particular experiment on Comet.ml.
      experiment_key: Optional. If set, restores from existing experiment.
      offline: If api_key and save_dir are both given, this determines whether
          the experiment will be in online or offline mode. This is useful if you use
          save_dir to control the checkpoints directory and have a ~/.comet.config
          file but still want to run offline experiments.
      prefix: A string to put at the beginning of metric keys.
      kwargs: Additional arguments like `workspace`, `log_code`, etc. used by
          :class:`CometExperiment` can be passed as keyword arguments in this logger.
  
  Raises:
      ModuleNotFoundError:
          If required Comet package is not installed on the device.
      MisconfigurationException:
          If neither ``api_key`` nor ``save_dir`` are passed as arguments.
  Example:
      >>> from anomalib.utils.loggers import AnomalibCometLogger
      >>> from pytorch_lightning import Trainer
      >>> comet_logger = AnomalibCometLogger()
      >>> trainer = Trainer(logger=comet_logger)
  
  See Also:
      - `Comet Documentation <https://www.comet.com/docs/v2/integrations/ml-frameworks/pytorch-lightning/>`__
code: def __init__(
      self,
      api_key: str | None = None,
      save_dir: str | None = None,
      project_name: str | None = None,
      rest_api_key: str | None = None,
      experiment_name: str | None = None,
      experiment_key: str | None = None,
      offline: bool = False,
      prefix: str = "",
      **kwargs,
  ) -> None:
      super().__init__(
          api_key=api_key,
          save_dir=save_dir,
          project_name=project_name,
          rest_api_key=rest_api_key,
          experiment_name=experiment_name,
          experiment_key=experiment_key,
          offline=offline,
          prefix=prefix,
          **kwargs,
      )
      self.experiment.log_other("Created from", "Anomalib")
  
file_path: anomalib/src/anomalib/utils/loggers/comet.py
imports: from __future__ import annotations
  from typing import Any
  import numpy
  from matplotlib.figure import Figure
  from pytorch_lightning.utilities import rank_zero_only
  from .base import ImageLoggerBase
label_desc: Use image node_id 1 to create a new AnomalibCometLogger object from inherited base classes: ImageLoggerBase, CometLogger with example: obj = AnomalibCometLogger(api_key, save_dir, project_name, rest_api_key, experiment_name, experiment_key, offline, prefix)